Business Intelligence for the Real Time Enterprise

August 26, 2013 - Riva del Garda, Trento, Italy


Keynote Speech #1
AsterixDB: A New Platform for Real-Time Big Data BI
by Michael J. Carey (Bren Professor of Information and Computer Sciences at UC Irvine)
Keynote Speech #2
Query Adaptation and Privacy For Real-time Business Intelligence
by Prof. Johann-Christoph Freytag ( full professor for Databases and Information Systems (DBIS) at the Computer Science Department of the Humboldt-Universität zu Berlin, Germany)

Keynote Speech #1

AsterixDB: A New Platform for Real-Time Big Data BI

AsterixDB is a full-function BDMS (Big Data Management System) with a uniquely rich feature set that distinguishes it from the other Big Data platforms that are available in today's open source Big Data ecosystem. We believe that its feature set makes it ideally-suited to modern needs such as web data warehousing, social data storage and analysis, and other real-time business intelligence (BI) use cases related to what we now commonly refer to as "Big Data". AsterixDB has:
* A flexible, semistructured NoSQL style data model (ADM) based on JSON
* A declarative query language (AQL) for expressing a wide range of BI queries
* A parallel runtime engine, Hyracks, that has been scale-tested to 1000's of cores
* Partitioned LSM-based data storage and indexing to support efficient new data intake
* Support for externally stored data (e.g., in HDFS) as well as natively managed data
* A rich set of primitive types, including spatial, temporal, and textual data types
* B+ tree, R tree, and inverted keyword (exact and fuzzy) secondary indexing options
* Support for fuzzy, spatial, and temporal queries as well as for parametric queries
* A notion of datafeeds to support continuous ingestion from relevant data sources
* Basic transactional capabilities akin to those of a NoSQL store
In this talk we will provide a technical overview of AsterixDB with an emphasis on the architectural and user-level features that are particularly relevant to Big Data use cases involving real-time BI. A Beta release of AsterixDB is now publically available via open source at

About the speaker

Michael J. Carey

Michael J. Carey is a Bren Professor of Information and Computer Sciences at UC Irvine. Before joining UCI in 2008, Carey worked at BEA Systems for seven years and served as the chief architect of (and an engineering director for) BEA's AquaLogic Data Services Platform product. Carey also spent a dozen years teaching at the University of Wisconsin-Madison, five years at IBM Almaden as a database researcher/manager, and a year and a half as a Fellow (and briefly the VP of Software) at e-commerce software startup Propel Software during the 2000-2001 Internet bubble. Carey is an ACM Fellow, a member of the National Academy of Engineering, and a past recipient of the ACM SIGMOD E. F. Codd Innovations Award. His current research interests center around data-intensive computing and scalable data management (a.k.a. Big Data).

Keynote Speech #2

Query Adaptation and Privacy For Real-time Business Intelligence

This talk discusses several technical and non-technical challenges and issues that need special attention when dealing with real-time business intelligence systems. While most keynotes of previous BIRTE Workshops focused on (database) technology this talk will take a more holistic view by covering technical and non-technical aspects.

First, we introduce and discuss several real-world applications to derive technical and non-technical requirements that are quite diverse in the context of real-time business intelligence. Based on those requirements and based on our experience in developing the Stratosphere database management system together with other research groups in Berlin, Germany, we outline our already existing and future techniques of query adaptation and of histogram building that are about to be implemented into Stratosphere to support real-time business intelligence.

In the second part of the talk we discuss important aspects of privacy when dealing with personal data, and outline necessary requirements for implementing real-time business intelligence systems to protect people's privacy (to some extent). It will become apparent that often there exists a trade-off between the level of privacy and the utility expected by those who perform real-time business analytics.

About the speaker

Johann-Christoph Freytag

Johann-Christoph Freytag is currently full professor for Databases and Information Systems (DBIS) at the Computer Science Department of Humboldt-Universität zu Berlin, Germany. Before joining the department in 1994, he was a research staff member at the IBM Almaden Research Center (1985-1987), a researcher at the European Computer-Industry-Research Centre (ECRC, in Munich, Germany, 1987-1989), and the head of Digital's Database Technology Center (also in Munich, 1990-1993). He holds a Ph.D. in Applied Mathematics/Computer Science from Harvard University, MA.

Prof. Freytag's research interests include all aspects of query processing and query optimization in object-relational database systems, new developments in the database area (such as semi-structured data, data quality, databases and security), privacy in database systems, and applying database technology to applications such as GIS, genomics, and bioinformatics/life science. In the last years he received the IBM Faculty Award four times for collaborative work in the areas of databases, middleware, and bioinformatics/life science. In 2009 and 2010 he also received the HP Labs Innovation Research Awards for research on DBMS and Cloud computing. In 2003 he organized the VLDB conference in Berlin and was a member of the VLDB Endowment (2001-2007) and in the head of the German database interest group (Fachbereich DBIS) of the GI (Gesellschaft für Informatik).